[Evaluation of sphygmomanometers used by family physicians practicing outside the hospital environment in Bas-Saint-Laurent].
Bibliographic record
Abstract
OBJECTIVE: To assess the precision and integrity of all aneroid and mercury sphygmomanometers regularly used by family physicians practising outside hospitals. DESIGN: Cross-sectional study. SETTING: Private medical clinics and local community health centres in Bas-Saint-Laurent, Qué. PARTICIPANTS: A total of 151 of the 166 physicians in this administrative region. MAIN OUTCOME MEASURES: Precision of the mercury sphygmomanometers was measured using the difference between a reading in the absence of pressure and level 0. Precision of the aneroid sphygmomanometers was measured using variations at pressures of 140 mm Hg and 90 mm Hg compared with those on a calibrated mercury sphygmomanometer. Integrity of sphygmomanometers, arm cuffs, and inflating bulbs was also assessed. RESULTS: In all, 258 sphygmomanometers met the inclusion criteria (111 mercury sphygmomanometers and 147 aneroid sphygmomanometers). Discrepancies of > or = 4 mm Hg were found in 15.5% of these instruments (12.6% and 17.7% of the mercury and aneroid sphygmomanometers, respectively). In 31.0% of the instruments (52.3% and 15.0% of the mercury and aneroid sphygmomanometers, respectively), one component was malfunctioning. CONCLUSION: Sphygmomanometers that measure patients' blood pressure inaccurately could result in an incorrect diagnosis of hypertension or in a normal blood pressure reading in a hypertensive patient.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".